Intelligence that translates data to human outcomes.
A leading cause of failure.
Unexpected toxicity should not decide which medicines reach patients.
Better early decisions, safer medicines.
Predict, explain, and fix drug toxicity early before it derails late-stage development.
The largest experimental-to-clinical dataset.
We did the lab work: tens of thousands of molecules profiled across exposure, cell biology, and metabolism linked to human clinical outcomes and mechanisms.
Translate
Contextualized, personalized next steps to advance great medicines forward.
Stop
High risk fitting BSEP/MDR3 binding pockets
- High lipophilicity
- Planar hydrophobic surface
- 4 aromatic rings
Advance
Reduced off-target binding risks
- Lower lipophilicity
- Higher 3D character
- Greater rotational freedom
Research
Learn more about our work
03/2026 Technical Summary
03/2026 Technical Report
A Better Proxy Than the Rat and Dog
Using AI to Combine Exposure, Metabolism, and Liver Function to Model DILI in Modern Molecules
Cell Painting for cytotoxicity and mode-of-action analysis in primary human hepatocytes
Counting cells can accurately predict small-molecule bioactivity benchmarks
Modeling and Interpreting Multiple Readouts for Clinical Liver Toxicity Risk Assessment
